In small and midsize harbours, boom cranes are used for multiple applications. These include bulk cargo handling and container transloading. An example for a boom crane used in small and midsize harbours with mixed freight types is depicted in FIG. 1. Currently, the level of process automation is comparatively low and container transloading is done manually by crane operators. However, the general trend of logistic automation in harbours requires higher container handling rates, which can be achieved by increasing the level of process automation.
On boom cranes, containers are mounted to the crane hook using spreaders (manipulators), see FIG. 2. Spreaders can only be locked to containers after they have been precisely landed on them. This means that the position and the orientation of the spreader have to be adapted to the container for successfully grabbing the container with the spreader. The spreader orientation, which is also defined as the skew angle, is controlled using a hook-mounted rotator motor.
Since wind, impact, and uneven load distribution can cause skew vibrations, an active skew control is desirable for facilitating crane operation, improving positioning accuracy, and increasing turnover. Positioning the spreader requires damping the pendulum oscillations, which can be done either manually by the operator or automatically using anti-sway systems. Adapting the spreader orientation requires damping the torsional oscillations (“rotational vibrations” or “skewing vibrations”) using a rotational actuator, which is regularly done manually.
A few technical solutions for a skew control are known from the state of the art and which are mostly designed for a gantry crane. Due to specific properties of such cranes these implementations of skew controls are mostly not compliant with differing crane designs. In particular boom cranes comprise a longer rope length and a much smaller rope distance which yields to lower torsional stiffness compared to gantry cranes. This increases the relevance of constraints and also results in lower eigenfrequencies. Second, arbitrary skew angles are possible on boom cranes, while gantry cranes can only reach skew angles of a few degrees. Third, the well-established visual load tracking mechanism of gantry cranes using cameras and markers cannot be applied to boom cranes.
For instance, a solution for a skew control system is known from EP 1 334 945 A2 performing optical position measurements (e.g. camera based) for detecting the skew angle. However, such system may become unavailable during night or during bad weather conditions.
Another method for controlling the orientation of the crane load is known from DE 100 29 579 and DE 10 2006 033 277 A1. There, the hook suspended on ropes has a rotator unit containing a hydraulic drive, such that the manipulator for grabbing containers can be rotated around a vertical axis. Thereby, it is possible to vary the orientation of the crane loads. If the crane operator or the automatic control gives a signal to rotate the manipulator and thereby the load around the vertical axis, the hydraulic motors of the rotator unit are activated and a resulting flow rate causes a torque. As the hook is suspended on ropes, the torque would result in a torsional oscillation of the manipulator and the load. To position the load at a specific angle, this torsional oscillation has to be compensated. However, the solutions known from DE 100 29 579 and DE 10 2006 033 277 A1 use linear models for describing the skew motion. Such linear models are only valid in a small neighborhood around the steady state, i.e. only small deflection angles can be used. Further, the systems known from DE 100 29 579 and DE 10 2006 033 277 A1 employ a state observer which needs the second derivative of a position measurement. Such a double differentiation is disadvantageous due to noise amplification. Furthermore, both systems known from DE 100 29 579 and DE 10 2006 033 277 A1 require knowledge of the load inertia which varies heavily with the load mass. Especially in DE 10 2006 033 277 A1, a time-consuming calculation method is used for estimating the load inertia.
It is the objection of the present disclosure to provide an improved method for controlling the skew angle of a crane, in particular of a boom crane.
The aforementioned object is solved by a method performed on a control unit of a crane comprising a manipulator for manipulating the orientation of a load connected by a rotator unit to a hook suspended on ropes. For improvement of the operating of the crane the skew angle of the load is controlled by a control unit of the crane.
In the following, a rotation of the manipulator (spreader) and/or crane load (e.g. container) around the vertical axis is described as skew motion. The heading or yaw of a load is called skew angle and rotation oscillations of the skew angle are called skew dynamics.
The expression hook defines the entire load handling devic excluding the spreader.
A control of the skew angle normally requires a feedback signal which is usually based on a measurement of the current system status. However, implementation of a skew control according to the present disclosure requires states of the boom crane which cannot be measured or which are too disturbed to be used as feedback signals.
Therefore, the present disclosure recommends that one or more required states are estimated on the basis of a model describing the skewing dynamics during the crane operation. Further, a nonlinear model is used for describing the skew dynamics of the crane during operation instead of a linear model as currently applied by known skew controls. Implementation of a non-linear model enables consideration of the non-linear behaviour of the skew dynamics over a wider range or the full range of the possible skewing angle of the load. Since boom cranes permit a significantly larger skewing angle than gantry cranes the present disclosure essentially improves the performance and stability of the skew control applied to boom cranes.
According to the present disclosure a non-linear model is used which allows using larger deflection angles (up to90°). Larger deflection angles yield larger reactive torques and therefore faster motion.
Further, the present disclosure does not require any optical sensors to improve the system availability and system reliability. No optical position measurement has to be performed for detecting the skew angle as known from the state of the art.
In the method for controlling the orientation of a crane load of the present disclosure, torsional oscillations are avoided by an anti-torsional oscillation unit using the data calculated by the dynamic non-linear model. This anti-torsional oscillation unit uses the data calculated by the dynamic non-linear model to control the rotator unit such that oscillations of the load are avoided. The anti-torsional oscillation unit can generate control signals that counteract possible oscillations of the load predicted by the dynamical model. The rotator unit includes an electric and/or hydraulic drive. The anti-torsional oscillation unit can generate signals for activating the rotator motor, thereby applying torque generated by a hydraulic flow rate or electric current.
In particular, the non-linearity included in the model describing the skew dynamics refers to the non-linear behaviour of the resulting reactive torque caused by torsion of the load, i.e. the ropes. For instance, the reactive torque increases until a certain skew angle of the load is reached, for instance of about 90 degrees. By excessing said certain skew angle the reactive torque decreases due to twisting of the ropes. The skew dynamic model optionally includes one or more non-linear terms or expressions representing the non-linear behaviour as described before.
Former controller architectures as described before require the mass of the load and most importantly, the moment of inertia of the load as an input parameter. However, the distribution of mass inside the load, e.g. a container, is unknown and therefore the moment of inertia of the load is not known, either. Therefore, known prior art control architectures estimate the moment of inertia of the load on the basis of a complex and computationally intensive process. According to an example aspect of the present disclosure the implemented non-linear model for estimation of the system state is independent on the load mass and/or the moment of inertia of the load mass. Consequently, the performance of the skew control significantly increases while reducing the processor load and usage of the control unit.
In particular, the method according to a further preferable aspect does not require a Kalman filter for estimation of the system state.
In an example embodiment of the present disclosure the estimated system state includes the estimated skew angle and/or the velocity of the skew angle and/or one or more parasitic oscillations of the skew system. A possible parasitic oscillation which influences the skew dynamics may be caused by the slackness of the hook, for instance. Further, system state may further include besides the estimates parameters several parameters which are directly or indirectly measured by measurement means of the crane.
The control unit may be based on a two-degree of freedom control (2-DOF) comprising a state observer for estimation of the system state, a reference trajectory generator for generation of a reference trajectory in response to a user input and a feedback control law for stabilization of the nonlinear skew dynamic model.
This means that a control signal for controlling the rotator drive of the rotator unit and/or a slewing gear and/or any other drive of the crane comprises a feedforward signal from the reference trajectory generator and a feedback signal to stabilize the system and reject disturbances. The feedforward control signal is generated by the reference trajectory generator and designed in such a way that it drives the system along a reference trajectory under nominal conditions (nominal input trajectory). Deviation from a nominal state (nominal state trajectory) defined by the reference trajectory generator are determined by using the estimated state determined by the state observer on the basis of the non-linear model for skew dynamics. Any deviation is compensated by a feedback signal determined from the nominal and estimated state using a feedback gain vector. The resulting compensated signal is used as the feedback signal for generation of the control signal.
For estimation of the system state considering the skew dynamics the state observer optionally receives measurement data comprising at least the drive position of the rotator unit and/or the inertial skewing rate and/or the slewing angle of the crane. These parameters may be measured by certain means installed at the crane structure. For instance, the drive position of the rotator may be measured by an incremental encoder. Since the incremental encoder gives a reliable measurement signal the drive speed may be calculated by discrete differentiation of the drive position. Further, a gyroscope may be installed at the hook, in particular the hook housing, for measuring the inertial skewing rate of the hook. Said gyroscope measurement may be disturbed by a signal bias and a sensor noise. The slewing angle of the crane may be measured by another sensor, for instance an incremental encoder installed at the slewing gear.
Furthermore, the rope length may be measured precisely and a spreader length used for grabbing a container may be derived from a spreader actuation signal. It may be possible to calculate the radius of gyration from the spreader length.
A good quality for estimation of the system state is achieved by using a state observer of a Luenberger-type. However, any other type of a state observer may be applicable.
The state observer may be implemented without the use of a Kalman filter since the model for characterizing the skew dynamic is independent of the load mass and/or the moment of inertia of the load mass.
As described before, the systems known from DE 100 29 579 and DE 10 2006 033 277 A1 employ a state observer which needs the second derivative of a position measurement. Such a double differentiation is disadvantageous due to noise amplification. According to an example aspect of the present disclosure the used coordinate system for describing the state of the system has been changed to an extent that the present disclosure does not require double differentiation.
It is advantageous when the reference trajectory generator calculates a nominal state trajectory and/or a nominal input trajectory which is/are consistent with the crane dynamics, i.e. skew dynamics and/or rotator drive dynamics and/or measured crane tower motion. Consistency with skew dynamics means that the reference trajectory fulfills the differential equation of the skew dynamics and does not violate skew deflection constraints. Consistency with drive dynamics means that the reference trajectory fulfills the differential equation of the drive dynamics and violates neither drive velocity constraints nor drive torque constraints.
A generation of the nominal state and input trajectory is optionally performed by using the non-linear model for the skew dynamics. That is to say that a simulation of the non-linear skew dynamic model and/or a simulation of the rotator unit model is/are implemented at the reference trajectory generator for calculation of a nominal state trajectory and/or a nominal input trajectory consistent with the aforementioned crane dynamics.
Further, a disturbance decoupling block of the reference trajectory generator decouples the skewing dynamics from the crane's slewing dynamics. That is to say that the slewing gear can still be manually controlled by the crane operator during an active skew control. The same may apply to the dynamics of the luffing gear. Consequently, the control of the skewing angle may be decoupled from the slewing gear and/or the luffing gear of the crane.
In a particular embodiment of the present disclosure the reference trajectory generator enables an operator triggered semi-automatic rotation of the load of a predefined angle, in particular of about 90° and/or 180°. That is to say the control unit offers certain operator input options which will proceed an semi-automatically rotation/skew of the attached load for a certain angle, ideally 90° and/or 180° in a clockwise and/or counter-clockwise direction. The operator may simply push a predefined button on a control stick to trigger an automatic rotation/skew of the load wherein the active skew control of the skew unit avoid torsional oscillations during skew movements.
The present disclosure is further directed to a skew control system for controlling the orientation of a crane load using any one of the methods described above. Such a skew control unit may include a 2-DOF control for the skew angle. The skew control system may include a reference trajectory generator and/or a state observer and/or a control unit for controlling the control signal of a rotator unit and/or slewing gear and/or luffing gear.
The present disclosure further comprises a boom crane, especially a mobile harbour crane, comprising a skew control unit for controlling the rotation of a crane load using any of the methods described above. Such a crane comprises a hook suspended on ropes, a rotator unit and a manipulator.
Advantageously, the crane will also comprise an anti-sway-control system that interacts with the system for controlling the rotation of a crane. The crane may also comprise a boom that can be pivoted up and down around a horizontal axis and rotated around a vertical axis by a tower. Additionally, the length of the rope can be varied.
Further advantages and properties of the present disclosure are described on the basis of embodiments shown in the figures.